Introduction

Let me start by thanking the University of Tasmania
and the Tasmanian branch of the Economic Society of
Australia for hosting this event.

Today I am going to talk about economic forecasting,
which plays an important role in policy deliberations
at the Reserve Bank of Australia (RBA). It assists in
interpreting economic developments and, because monetary
policy typically affects economic activity and inflation
with a lag, it is a necessary part of determining and
communicating the appropriate stance of policy.

I'm also going to discuss the results of an external
review of our forecasting methods and processes, which
we have just published, and our responses to the recommendations
therein.

Our current approach to forecasting has been in place
for some years. While it has served us well, we thought
it was time to consider whether our methods and processes
would continue to be appropriate and how we might improve
upon them. To do this, we commissioned two eminent economists
to conduct a review, Professor Adrian Pagan of the University
of Sydney and Dr David Wilcox of the Federal Reserve
Board of Governors.[1]

The Existing Approach to Forecasting at the RBA

The process of economic forecasting actually involves
a wide range of activities. The most familiar relates
to the construction of forecasts that reflect our best
estimates of future economic outcomes.[2]
Each quarter in the Statement on Monetary Policy,
we publish forecasts for Australia's major trading
partners' GDP growth, as well as Australia's
terms of trade, GDP growth, unemployment rate and inflation
over the next two-and-a-half years. However, these numbers
are just a summary of an extensive process in which
our analysts incorporate incoming data, assess the relevance
of new events, construct forecasts for a large number
of economic variables, analyse various scenarios and
consider a range of key risks to the outlook. All of
this provides a useful framework to guide policy deliberations
and then communicate those decisions.

This process may lead us to revise the economic outlook
– either in response to unexpected developments or shocks,
or to news that changes our views on how the economy
is evolving. If a change in the outlook is judged to
be significant, it may warrant a change in the stance
of monetary policy. However, that link between the forecasts
and policy is by no means a mechanical one. In part,
that is because any policy response will depend on the
nature of the change to the outlook, including whether
it has been driven primarily by supply or demand shocks,
and how persistent those shocks are likely to be. Also,
any policy response will depend on an assessment of
the extent to which the economy will adjust of its own
accord. It is important to recognise that sufficiently
flexible economies can do much to right themselves,
with households and businesses responding to the signals
provided by changes in prices, wages and the exchange
rate. Such changes have played a major role in the adjustment
of the Australian economy to the decline in commodity
prices and mining investment over recent years.[3]
Another important consideration
is the sizeable degree of uncertainty about the outlook.
While a revision to the central outlook might appear
to be of substance, it may still be relatively small
compared with the considerable degree of forecast uncertainty.
And finally, other considerations, beyond the near-term
outlook of the macroeconomy, may be relevant, including
the prospects for financial stability.

The role of models

Modelling can play a useful role in the forecasting
process, including by helping to identify the nature
of the shocks affecting the economy. Models can also
provide a sense of how the economy might respond to
alternative policy paths or different assumptions about
key variables, such as commodity prices or the exchange
rate to name just two. In addition, models allow us
to check whether our forecasts are consistent. For example,
does the path for output and employment imply a plausible
path for productivity? And do they imply patterns of
economic behaviour that are broadly in line with historical
experience? A recent instance is the decline in wage
growth over recent years, which has been larger than
implied by the historical relationship with the unemployment
rate. Of course, we may be justified from time to time
to think that history is likely to be a poor guide,
but it's worth being explicit about any such deviations.
Finally, while models play an important role in the
forecasting process, the value of models should not
be overstated, particularly because no one model that
we have captures all of the relevant features of an
economy or consistently ‘beats’ other forecasts.[4]

Central forecasts

Central forecasts attract a great deal of attention
and commentary from financial market participants, the
press and the general public. The extent of that attention
is often unwarranted. As several of my colleagues have
noted over the years, point forecasts should be treated
with a healthy degree of scepticism.[5]
It is unlikely that GDP growth or inflation will exactly
match point forecasts, or even narrow ranges around
those points. Instead, central forecasts are best thought
of as our view of the most likely of a wide range of
possible outcomes, with small changes in the forecasts
unlikely to reflect anything more than a modest shift
in the balance of risks.

To avoid fallacies that can accompany false precision,
we recently altered what we refer to as ‘Table 6.1’
of the forecasts in the Statement by presenting
ranges for GDP and inflation in ½ percentage
point increments, rather than ¼ percentage
point increments (shown below). No doubt that will not
discourage some readers from using their rulers to measure
the graphs and focus on revisions down to the nearest
0.1 percentage point! Also, some commentators will
be tempted to draw attention to what they might describe
as ‘large ½ percentage point changes’
when the forecasts are revised, even though any such
revisions may reflect much smaller adjustments if it
is the case that the forecasts have merely crossed rounding
barriers.[6] The
key point I'd like to make here is that if we
judge any forecast revision to be of substance worth
noting, we'll note it!

To emphasise this point further, it is worth remembering
that the available data are subject to a degree of measurement
error. In the case of real GDP, for example, quarterly
growth rates can easily be revised up or down by ½ percentage
point or more in the first four years after the initial
estimate (Graph 1).[7]
The recent revision to GDP growth – of 0.2 percentage
points in the September quarter of 2015 – was relatively
minor, though the data now suggest that GDP growth picked
up in the second half of 2015 to be more in line with
the strength that was apparent in a range of indicators
of the labour market and business conditions at that
time.

Graph 1

Starting points

A critical element of forecasting is to have a sense
of where the economy is now and in which direction it's
currently heading. This comes from carefully dissecting
the incoming economic data in an attempt to disentangle
signals from noise and determine the extent to which
shocks will be long-lived or transitory.[8]
In addition to publicly available data, we make use
of information obtained from our business liaison program.
We also use information gleaned from econometric models,
which include both single-equation models of individual
variables as well as larger models that attempt to capture
the behaviour of multiple variables simultaneously.

The various information sources that we use don't
always provide a clear message about where we are and
where we are heading. Indeed, it is naïve to think that
the truth can reside in a single source of data or a
particular model. To an extent, this reflects the usual
noise in the various types of information, as well as
uncertainty about the strength of different economic
relationships. Combining information from a variety
of sources, and models, typically results in more robust
conclusions than relying exclusively on a single source.

The behaviour of inflation provides a timely example.
A wide range of information suggests that inflation
is low and likely to remain so over the next couple
of years. This includes both structural (DSGE) and statistical
(VAR) models of inflation. These attribute the outcomes
over the past year or more, in part, to the influence
of foreign ‘factors’ – as captured by low
inflation and low interest rates in the advanced economies.
These can have a direct effect on inflation in Australia
via the prices of imports. There are indirect effects
as well, whereby spare capacity in product and labour
markets globally may have contributed to relatively
low inflation and wage outcomes in Australia. The models
suggest that these influences on Australian inflation
are typically quite persistent, which reinforces the
message from other sources that inflation is likely
to remain low for some time.

Uncertainties

For several years we have presented confidence intervals
for GDP growth and inflation forecasts in the Statement
(Graph 2).[9] These
summarise the extent of uncertainty based on previous
forecast errors. Since February of last year, we have
also published an unemployment rate forecast and confidence
intervals around that.

Graph 2

In addition to confidence intervals, the forecasting
process leads us to think about the risks associated
with specific economic developments and to quantify
those where possible. Each quarter, we discuss a range
of scenarios that explore how the economy might respond
under conditions that vary from the central case. For
example, what if commodity prices, the exchange rate
or overseas economic conditions evolve differently to
the paths embedded in our central forecasts? These exercises
help us to identify events that could have a meaningful
effect on the economy and to which policymakers may
need to respond.

Background to the Pagan-Wilcox Review

We commissioned Adrian Pagan and David Wilcox to conduct
a review of forecasting in Economic Group in late 2014.
We asked for their views on whether there were areas
we could improve upon, whether the tools of forecasting
were the right ones and whether we were using the forecasts
appropriately. We did not commission the Review as a
result of any concerns about our recent forecasting
experience or because we felt that our existing procedures
were fundamentally flawed. But it was time for a careful
health check of our approach.

Professor Pagan and Dr Wilcox visited the Bank for two
weeks during one of our regular forecasting rounds.
They spent time with individual sections in Economic
Group, examining our models and forecasting approaches
in detail. They also met with senior management and
attended our internal forecast discussions.

Their review represents a thorough analysis of our forecasting
procedures. We have made it publicly available today.
I will attempt to summarise its key conclusions and
describe how we have responded to the recommendations.

The Review's Conclusions and Recommendations

The Review concluded that our forecasting practices
were fundamentally sound and produced information conducive
to good policymaking. The reviewers praised the knowledge,
motivation and technical proficiency of our analysts.
They also commended the use of models and the spirit
of open debate in our internal forecasting discussions.

But there is always room to improve. The Review made
a number of recommendations, which can be summarised
in three categories: the development of new models;
changes to forecast procedures; and organisational changes.

Development of new models

There were two recommendations regarding the modelling
tools we used.

First, the Review recommended that we put additional
resources into developing and analysing ‘full-system’
or ‘general equilibrium’ models of the economy
– that is, models which account for the simultaneous
responses of a large number of key variables to unexpected
developments (or shocks).
The Review recommended supplementing our existing models
with one that incorporates our separate single equation
estimates for a range of key variables into a system
of equations.[10]

Second, the Review noted the enormous changes to the
structure of the Australian economy over the past decade
or more, particularly, but not exclusively, related
to the mining boom. These developments caused shifts
in the composition of economic activity, such as the
large pick-up in mining investment that peaked in 2012.
Hence, the relationships between economic variables
may be different from the past. The Review recommended
placing more emphasis on investigating the robustness
of existing economic models to structural change and
provided a number of suggestions on how to do this.[11]

Changes to existing forecast procedures

The Review also recommended some modifications to some
of our forecast procedures.

Forecast horizon

It suggested we consider extending the forecasting horizon
beyond two-and-a-half years. It was acknowledged that
doing so would be more straightforward when using model-based
forecasts. Moreover, the current approach has a number
of advantages. A two-to-three year horizon is a period
over which monetary policy, and what could broadly be
termed ‘demand-side’ factors, tend to influence
economic activity. Over longer horizons, ‘supply-side’
influences, like changes in the trend rate of productivity
growth or the non-accelerating inflation rate of unemployment
(NAIRU), are likely to be more important. These factors
are more difficult to forecast than short-run, demand-side
influences, and are not affected by monetary policy
decisions.

However, following large and persistent disturbances,
such as a once-in-a-century boom in commodity prices,
the economy may not return to its steady state within
the existing forecasting horizon. This could complicate
the assessment of whether current policy settings are
appropriate, hence the recommendation to extend the
horizon.

Cash rate paths

Another recommendation was related to a ‘technical
assumption’ about the cash rate that underpins
our forecasts. At the time of the Review, we typically
assumed that the cash rate would remain constant across
the forecast horizon.[12]
This has the advantage of simplicity. Also, over short
horizons it often provides a reasonable approximation
to what econometric models and financial market participants
would expect. However, over longer horizons a constant
cash rate assumption may be less plausible, particularly
when interest rates are far from average levels. The
Review recommended considering alternatives to a constant
cash rate assumption. A number of alternatives exist,
including: the path implied by financial market prices;
a path consistent with the past behaviour of the Bank
as summarised by an estimated ‘monetary policy
rule’; or an ad hoc path postulated by
staff members. There is no consensus about which of
these alternatives is optimal.[13]

Broaden discussion of the forecasts

The Review also made suggestions relating to the presentation
of our forecasts in the Statement. In particular,
the authors recommended that we publish a forecast for
the unemployment rate. They noted that to assess the
state of the real economy it is not sufficient to know
the pace of GDP growth; one also needs to know how this
rate of growth relates to potential growth and hence
the extent to which spare productive capacity is rising
or falling. While we have always focused on these concepts
in our internal analysis, publishing unemployment rate
forecasts provides useful information in this regard.

Discussion of the risks

An additional suggestion was to alter our discussion
of risks to the forecasts in the Statement. The
Review argued that there was scope to provide more
guidance on the plausibility and implications of alternative
scenarios, rather than merely providing a list of events
that could affect the outlook.

It is possible to come up with any number of scenarios
that may cause economic outcomes to differ from a given
set of forecasts. It is worth noting, however, that
many plausible scenarios may have fairly benign implications.
To give one example, we typically condition our forecasts
on a constant exchange rate, even though it would be
unusual for the exchange rate to remain steady for any
length of time. However, the effect of an exchange rate
movement will depend in large part on whether it has
occurred in response to other developments, such as
a change in commodity prices. The consequences of such
exchange rate movements are predictable to some degree
and, in many instances, have tended to help insulate
the economy from adverse developments offshore or even
domestically. In other circumstances, a large exchange
rate movement (or even a lack of movement in the face
of other developments) may represent an important shock
to the economy.

One can also imagine scenarios that are unlikely to
occur but may have far more substantial implications
for the economic outlook if realised. These scenarios
can be difficult to quantify but may be worth discussing
nonetheless. An example that we discussed in our most
recent Statement was the potential for financial
instability in China to lead to a sharp slowdown in
economic activity there and in the Asian region more
broadly.

Organisational suggestions

Finally, the Review made some recommendations regarding
the organisation of Economic Group.

The first was to establish a section dedicated to the
development and use of full-system macroeconomic models.
It would build upon the work of the existing modelling
team and develop a new model. The establishment of such
a section would facilitate the greater use of models
within the Bank, increase cooperation between different
sections generating the forecasts and help to enhance
the familiarity of our staff with these types of models.

The Review also encouraged the Bank to consider whether
existing hiring and staffing policies encouraged the
right mix of generalists and technical specialists.
In particular, it highlighted macroeconomic modelling
as an area requiring technical expertise. In addition,
the Review questioned whether personnel across Economic
Group were distributed optimally, with the suggestion
that more staff could be dedicated to modelling if there
were fewer staff monitoring overseas economies and/or
participating in the Bank's Regional and Industry
Analysis section, which conducts liaison across the
country.

Responses to the Review

My colleagues and I have spent time discussing the Review's
conclusions, re-examining our existing procedures and
developing appropriate responses.

We have already implemented some of the Review's
recommendations:

We have added a quantitative discussion of our unemployment
rate forecasts to the Statement, with a graph
of confidence intervals to illustrate the extent of
uncertainty.

The Statement's Outlook chapter now provides
a more comprehensive explanation of the uncertainties
around our forecasts, including more information about
the channels through which risks could affect the economy.

We have changed the nature of the cash rate assumption
underpinning our forecasts. Since the start of 2015,
we have conditioned our forecasts on the assumption
that the cash rate moves broadly in line with the path
implied by financial market pricing.

To increase the Bank's capacity to use full-system
models, we have established a new Macroeconomic Modelling
section within the Economic Analysis Department. This
has primary responsibility for generating model-based
analysis to enhance the quality of our forecasting processes
and policy advice. I should emphasise that this section
will complement our existing forecasting processes,
not replace them. As is the case at many other central
banks, our forecasts will still be generated by a range
of analysts and will feature a degree of judgement,
rather than be mechanical, model-based forecasts. However,
the forecasts will be usefully informed by the insights
and analysis that full-system models can provide.

The Review recommended redirecting resources from monitoring
overseas economies and conducting business liaison to
other activities, particularly modelling. However, we
have sourced staff for the new modelling section from
across Economic Group more broadly and have no intention
of reducing the extent of our liaison program. This
reflected our assessment that the benefits of monitoring
overseas economies and conducting domestic economic
liaison go well beyond the direct contribution to our
quarterly forecasting process.[14]
In addition, the liaison program provides valuable insights
for forecasting. For example, during the mining investment
boom, liaison provided timely and accurate information
about construction projects that was not available elsewhere.
Combining our liaison on each project has provided a
reasonably accurate picture of what has transpired.
Moreover, because a commodity price boom of this magnitude
had not been experienced before, models estimated using
historical data would have had difficulty anticipating
the extent of the response of mining investment. Similarly,
our analysts monitoring overseas economies help us to
understand the economic and financial developments affecting
our trading partners, particularly in the Asian region,
in a way that would not be possible from using publicly
available forecasts of a limited range of variables
such as GDP and inflation from organisations like the
International Monetary Fund or Consensus Economics.

Conclusion

The Pagan-Wilcox Review was a comprehensive health check
of our forecasting approach. While the Review confirmed
that our methods are fundamentally sound, it provided
a number of valuable suggestions for how we could improve
the way we forecast. We have already responded to many
of the suggestions and are in the process of following
up on others. While these changes are unlikely to see
much of an improvement in forecast accuracy, they have
the potential to enhance the role that forecasting plays
in the policy process and facilitate the usefulness
of the forecasts as an important tool of communication.

Endnotes

I thank Daniel Rees, who provided invaluable assistance in preparing these remarks, and
is the Head of the Bank's new Macroeconomic Modelling Section (see below).
[*]

Professor Pagan is one of Australia's foremost academic
economists and served on the Board of the Reserve Bank
from 1995 to 2000. Dr Wilcox is Director of the Division
of Research and Statistics at the Federal Reserve Board
of Governors in the United States.
[1]

I use the term ‘forecast’ somewhat loosely, since
these are conditioned on a range of assumptions, such
as a fixed nominal exchange rate and a particular path
for the cash rate, and hence could better be described
as ‘projections’.
[2]

Models usually involve some reasonable simplifications of reality so
as to make them tractable and possible to estimate.
Such models will be unable to capture all relevant considerations
all of the time.
[4]

To be clear, if an initial forecast of a particular number had been
close but less than say 2¼ per cent, for example,
it would have been rounded down to 2 per cent, but a
minor upward revision of less than ½ percentage
point could mean it subsequently rounds up to 2½
per cent.
[6]

Lowe P (2010), ‘Forecasting
in an Uncertain World’, Address to the Australian
Business Economists Annual Forecasting Conference, Sydney,
8 December, describes the inputs into the forecast process
in greater detail.
[8]

I should note that full-system models of one sort or another
have a long history at the Bank and already play a role
in the forecasting process. The earliest examples of
such models date back as far as the 1970s and include
the RBA1 model (Henderson J and P Norman (1975), ‘The
Equations of the RBA1/74 Model of the Australian Economy’,
RBA Research Discussion Paper No 7504) and the RBA76
model (Jonson P, E Moses and C Wymer (1976), ‘A
Minimal Model of the Australian Economy’, RBA
Research Discussion Paper No 7601). In the late 1990s,
Economic Research Department staff constructed a small
empirical model of the Australian economy. This model
was documented in Beechey M, N Bharucha, A Cagliarini,
D Gruen and C Thompson (2000), ‘A
Small Model of the Australian Macroeconomy’,
RBA Research Discussion Paper No 2000-05 and Stone A,
T Wheatley and L Wilkinson (2005), ‘A
Small Model of the Australian Macroeconomy: An Update’,
RBA Research Discussion Paper No 2005-11. More recently,
our staff have developed more complex dynamic stochastic
general equilibrium (DSGE) models. These models were
documented in Jääskela J and K Nimark (2011), ‘A
Medium-scale New Keynesian Open Economy Model of Australia’, Economic
Record (87),
pp. 11–36 and Rees D,
P Smith and J Hall (2015), ‘A
Multi-sector Model of the Australian Economy’,
RBA Research Discussion Paper No 2015-07. These sorts
of models feature in our internal forecast meetings.
However, I think it is fair to say that full-system
models have not been fully integrated into our forecasting
procedures and the nature of those models has been somewhat
distinct from the single-equation models that most of
our analysts work with day-to-day.
[10]

For example, by estimating models incorporating time-varying coefficients
or using techniques such as exponential smoothing that
reduce the weight given to certain observations when
estimating the parameters of a model.
[11]

However, we have used different conditioning assumptions at various
times. For example, during the global financial crisis
we conditioned our forecasts on financial market interest
rate expectations.
[12]

Some central banks, including the Bank of England and the European
Central Bank, condition their forecasts on paths implied
by financial market prices; others, including the Sveriges
Riksbank and the Norges Bank, condition their forecasts
on staff expectations of the future policy interest
rate.
[13]

Liaison information helps fill information gaps to strengthen
the Bank's capacity to assess structural trends in the
Australian economy. Two recent examples of this include
better understanding the responsiveness of the construction
sector to changes in interest rates and whether this
has changed over time, and understanding why non-mining
business investment has not picked up as forecast. The
State Offices also play a key role in enhancing the
Bank's engagement with the public via presentations
on economic developments to businesses and community
organisations, teacher conferences, and university and
school students across the country. For more information
about the role of the RBA's Business Liaison program
see RBA (2014), ‘The RBA's Business Liaison
Program’, RBA Bulletin (September), pp.
1-6 and Heath A (2015), ‘The
Role of the RBA's Business Liaison Program’,
Address to the Urban Development Institute of Australia,
Perth, 24 September.
[14]